require("dplyr")

## Set working directory
## to Dataverse folder

survey <- read.table("Harris_Data/Harris 1998 Business Week National Issues Survey, study no. 718368/harris_s718368_spss.tab", header = TRUE)

### fix everything below for this survey 

# pid
survey$pid <- c(1:nrow(survey))

# study 
survey$study <- "718368"

# study year (year)
survey$year <- 1998

# geographic data (urban)
table(survey$PLACE)
survey$urban <- dplyr::recode(survey$PLACE,
                       `1` = "Central City",
                       `2` = "Rest of metro area",
                       `3` = "Small town",
                       `4` = "Rural")
table(survey$urban)

# geographic data (region)
table(survey$REGION)
survey$region <- dplyr::recode(survey$REGION,
                        `1` = "East",
                        `2` = "East",
                        `3` = "South",
                        `4` = "South",
                        `5` = "Midwest",
                        `6` = "Midwest",
                        `7` = "West",
                        `8` = "West")
table(survey$region)

# respondent head of household (hh)
survey$hh <- NA

# increasing inequality (inequality)
table(survey$Q40_B)
survey$inequality <- dplyr::recode(as.character(survey$Q40_B),
                            `1` = "Feel",
                            `2` = "Don't Feel",
                            `11` = "Not Sure",
                            `12` = "Refused")
table(survey$inequality)

# inequality variable (inequality.variable)
survey$inequality.variable <- 1

# union (union.self)
survey$union.self <- NA
survey$union.other <- NA

# employment (employed)
survey$employed <- NA

# empl self
survey$employed.self <- NA

# occupation
survey$occupation <- NA

# occ self
survey$occupation.self <- NA

# household size (hhsize)
table(survey$Q2001)
survey$hhsize_over18 <- as.numeric(survey$Q2001)
survey$hhsize_under18 <- as.numeric(survey$Q2005)
survey$hhsize <- rowSums(survey[, c("hhsize_over18",
                                    "hhsize_under18")],
                         na.rm = TRUE)
survey$hhsize[is.na(survey$hhsize_over18)] <- NA

# education (educ)
table(survey$Q2015)
survey$educ <- dplyr::recode(survey$Q2015,
                      `1` = "Less than high school",
                      `2` = "High school graduate",
                      `3` = "Some college",
                      `4` = "College graduate",
                      `5` = "Post graduate",
                      `11` = "Not sure",
                      `12` = "Refused")
table(survey$educ)

# household income (income)
table(survey$Q2030)
survey$income <- dplyr::recode(survey$Q2030,
                        `1` = "Under $7500",
                        `2` = "$7,501 to $15,000",
                        `3` = "$15,001 to $25,000",
                        `4` = "$25,001 to $35,000",
                        `5` = "$35,001 to $50,000",
                        `6` = "$50,001 to $75,000",
                        `7` = "$75,001 to $100,000",
                        `8` = "$100,001 or over",
                        `11` = "Not sure",
                        `12` = "Refused")
table(survey$income)

# age
table(survey$Q2010)
survey$age <- as.character(survey$Q2010)

# race
table(survey$Q2040)
survey$race1 <- dplyr::recode(survey$Q2040,
                      `1` = "White",
                      `2` = "Black",
                      `3` = "African-American",
                      `4` = "Asian or Pacific Islander",
                      `5` = "American Indian or Alaskan native",
                      `6` = "Some other race",
                      `11` = "Not sure",
                      `12` = "Refused")
survey$race2 <- dplyr::recode(survey$Q2035,
                              `12` = "Decline/not sure",
                              `11` = "Decline/not sure",
                              `1` = "Yes, hispanic",
                              `2` = "No, not hispanic")
table(survey$race1)
table(survey$race2)
survey$race <- ifelse(survey$race1 == "Refused" |
                        survey$race1 == "Not sure", 
                      "Decline/not sure", ifelse(survey$race1 == "White",
                                                 ifelse(survey$race2 == "Decline/not sure",
                                                        "Decline/not sure",
                                                        ifelse(survey$race2 == "No, not hispanic",
                                                               "Non-Hispanic White",
                                                               "Hispanic White")), "Non-white"))
table(survey$race)
table(survey$race[survey$race1 == "White"])

# politics (party)
table(survey$Q2020)
survey$party <- dplyr::recode(survey$Q2020,
                       `1` = "Republican",
                       `2` = "Democrat",
                       `3` = "Independent",
                       `4` = "Other",
                       `11` = "Not sure",
                       `12` = "Refused")
table(survey$party)

# politics (ideology)
table(survey$Q2025)
survey$ideology <- dplyr::recode(survey$Q2025,
                          `1` = "Conservative",
                          `2` = "Moderate",
                          `3` = "Liberal",
                          `11` = "Not sure",
                          `12` = "Refused")
table(survey$ideology)

# gender
table(survey$Q2060)
survey$gender <- dplyr::recode(survey$Q2060,
                        `1` = "Male",
                        `2` = "Female")
table(survey$gender)

# religion
survey$religion <- NA

#factuals
table(survey$Q10)
survey$factual1 <- dplyr::recode(survey$Q10,
                          `1` = "Aware",
                          `2` = "Not aware",
                          `11` = "Don't know")
table(survey$factual1)
survey$factual2 <- NA
survey$factual3 <- NA

## alienation index
survey$dontcare <- dplyr::recode(survey$Q40_A,
                                 `1` = "Feel",
                                 `2` = "Don't Feel",
                                 `11` = "Not Sure",
                                 `12` = "Refused")
survey$dontcount <- dplyr::recode(survey$Q40_C,
                                  `1` = "Feel",
                                  `2` = "Don't Feel",
                                  `11` = "Not Sure",
                                  `12` = "Refused")
survey$leftout <- dplyr::recode(survey$Q40_D,
                                `1` = "Feel",
                                `2` = "Don't Feel",
                                `11` = "Not Sure",
                                `12` = "Refused")

## question_place
survey$question_place <- "before party"

# subset
survey_718368 <-survey[,c("pid", "study", "year", "urban", "region", "hh",
                          "inequality", "inequality.variable", "union.self", "union.other",
                          "employed", "employed.self", "occupation", "occupation.self", "hhsize", "educ", "income", 
                          "age", "race", "party", "ideology", "gender", "religion",
                          "factual1", "factual2", "factual3", "dontcare", "dontcount", "leftout",
                          "question_place")]


# save file
#saveRDS(survey_718368, file = "Harris_Data/survey_718368.rds")
